Video surveillance systems can be used to track objects appearing in videos. Surveillance video can also be used to search for objects, including people, appearing in a video. Modern video equipment can produce enormous quantities of data, which is time-consuming, costly and inefficient to manually review. Machine learning and computer vision technology can be used to aid in surveillance. However, surveillance tasks such as person re-identification typically require training of models based on supervised machine learning, which relies on manual frame-by-frame review of video frame data by a human operator to annotate individual images. Use of such systems can therefore be expensive.